Modeling gene-regulatory networks to describe cell fate transitions and predict master regulators
Artikel i vetenskaplig tidskrift, 2018

Complex organisms originate from and are maintained by the information encoded in the genome. A major challenge of systems biology is to develop algorithms that describe the dynamic regulation of genome functions from large omics datasets. Here, we describe TETRAMER, which reconstructs gene-regulatory networks from temporal transcriptome data during cell fate transitions to predict “master” regulators by simulating cascades of temporal transcription-regulatory events.

Författare

Pierre-Etienne Cholley

Chalmers, Biologi och bioteknik, Systembiologi

Universite de Strasbourg

CSBI

Julien Moehlin

Universite de Strasbourg

Alexia Rohmer

Universite de Strasbourg

Vincent Zilliox

Universite de Strasbourg

Samuel Nicaise

Universite de Strasbourg

Hinrich Gronemeyer

Universite de Strasbourg

Marco Antonio Mendoza-Parra

Genomique Metabolique

Universite de Strasbourg

npj Systems Biology and Applications

2056-7189 (eISSN)

Vol. 4 1 29

Ämneskategorier

Utvecklingsbiologi

Bioinformatik (beräkningsbiologi)

Bioinformatik och systembiologi

DOI

10.1038/s41540-018-0066-z

Mer information

Senast uppdaterat

2018-09-13